FaceFinger: Embracing Variance for Heartbeat Based Symmetric Key Generation System

Symmetric key generation methods are recently designed for wireless communication based on similar and unique observations of sensor measurements, such as wireless radio channels, inaudible sound channels, etc. Heartbeats, as unique biometrics, have been used for symmetric key generation. However, current solutions are designed for wearable devices with the integration of the same types of touchable heartbeat measurement equipment and fail because of the significant difference from different devices or the same devices with different deployment locations, which limits its large scale of deployment and application. To solve this problem, we propose a general heartbeat-based symmetric key generation solution by embracing observation variance from different devices, i.e. using an optical heart sensor on one finger and facing the camera of the second device to the user's face. We propose a novel data processing method to mitigate the significant difference and exploit key reconciliation to generate symmetric keys for paring devices and securing wireless communication. We have conducted extensive evaluations and shown our proposed method has good key matching rates up to 100% as well as good randomness. Security analysis has also been conducted to ensure the robustness of the proposed method.

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